System and method for estimating positioning error within a wlan-based positioning system

ABSTRACT

In one embodiment, a technique is provided for estimating and using an expected error of a position estimate of a WLAN-enabled mobile device produced by a WLAN positioning system. The WLAN-enabled mobile device receives signals transmitted by a plurality of WLAN access points in range of the WLAN-enabled device. The position of the WLAN-enabled device is estimated based on the received signals from the WLAN access points in range of the WLAN-enabled device. An expected error of the position estimate is based on at least one of a spatial spread associated with geographic positions of the WLAN access points, signal coverage areas of the WLAN access points, or a number of the WLAN access points. The expected error is used in providing one or more location-based services to a user of the WLAN-enabled mobile device.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.14/558,320 entitled System and Method For Estimating Positioning ErrorWithin A WLAN-Based Positioning System, filed Dec. 2, 2014 which is acontinuation of U.S. patent application Ser. No. 13/206,028, entitledSystem and Method For Estimating Positioning Error Within A WLAN-BasedPositioning System, filed Aug. 9, 2011, now U.S. Pat. No. 8,909,245,which is a continuation of U.S. patent application Ser. No. 12/966,001,entitled System and Method For Estimating Positioning Error Within AWLAN-Based Positioning System, filed Dec. 13, 2010, now U.S. Pat. No.8,019,357, which is a continuation of U.S. patent application Ser. No.11/625,450, entitled System and Method For Estimating Positioning ErrorWithin A WLAN-Based Positioning System, filed Jan. 22, 2007, now U.S.Pat. No. 7,856,234, which claims the benefit under 35 U.S.C. §119(e) ofU.S. Provisional Patent Application Ser. No. 60/864,716, filed on Nov.7, 2006, entitled Estimating Positioning Error for a WLAN BasedPositioning System, all of which are herein incorporated by reference intheir entirety.

This application is related to the following U.S. patent applications,the contents of which are hereby incorporated by reference:

-   -   U.S. patent application Ser. No. 11/261,987, entitled Method and        System for Building a Location Beacon Database, filed on Oct.        28, 2005, now U.S. Pat. No. 7,403,762;    -   U.S. patent application Ser. No. 11/430,079, Estimation Of Speed        and Direction of Travel In A WLAN Positioning System, filed on        May 8, 2006, now U.S. Pat. No. 7,835,754;    -   U.S. patent application Ser. No. 11/430,064, Estimation of Speed        and Direction of Travel In A WLAN Positioning System Using        Multiple Position Estimations, filed on May 8, 2006, now U.S.        Pat. No. 7,551,929;    -   U.S. patent application Ser. No. 11/430,222, Estimation of        Position Using WLAN Access Point Radio Propagation        Characteristics In a WLAN Positioning System, filed on May 8,        2006, now U.S. Pat. No. 7,515,578; and    -   U.S. patent application Ser. No. 11/430,224, Calculation of        Quality of WLAN Access Point Characterization for Use In a WLAN        Positioning System, filed on May 8, 2006, now U.S. Pat. No.        7,551,579.

BACKGROUND

1. Field of the Invention

The invention generally relates to estimating error in a WLAN-basedpositioning system and, more specifically, to determining the expectederror of an estimated position of a WLAN-enabled mobile device usingWLAN-based positioning system.

2. Discussion of Related Art

Estimation is the process of finding the most probable value for atarget parameter(s) based on a set of observable samples, which arecorrelated with the target parameter(s). Accuracy of the estimation canvary based on the quality of the observed samples. Quantifying thequality of estimation is one of the main subjects in estimation theory,and in most of the cases, it is an even harder problem than estimatingthe target parameter. A satellite based positioning system is one of theearly systems that was introduced for global positioning, and for thesame reason it is called Global Positioning System (GPS). In the GPSnetwork, accuracy of estimation is also determined and reported to endusers. The estimation error in the GPS network is presented in differentways. The error estimation is determined by considering the entirenetwork, and it is called Delusion Of Precision (DOP) for horizontal andvertical error. The DOP value is an indicator of error, and it can betranslated to error in meters as well.

Metro wide WLAN-based positioning systems have been explored by a coupleof research labs, but none of them provided an expected error ofposition estimation. The most important research efforts in this areahave been conducted by PlaceLab (a project sponsored by Microsoft andIntel), University of California San Diego ActiveCampus project(ActiveCampus—Sustaining Educational Communities through MobileTechnology, technical report #CS2002-0714), and the MIT campus widelocation system.

There have been a number of commercial offerings of WLAN locationsystems targeted at indoor positioning. (See, e.g., KavithaMuthukrishnan, Maria Lijding, Paul Havinga, Towards Smart Surroundings:Enabling Techniques and Technologies for Localization, Proceedings ofthe International Workshop an Location and Context-Awareness (LoCA 2005)at Pervasive 2005, May 2005, and Hazas, M., Scott, J., Krumm, J.:Location-Aware Computing Comes of Age, IEEE Computer, 37(2):95-97,February 2004 005, Pa005, Pages 350-362.) These systems are designed toaddress asset and people tracking within a controlled environment like acorporate campus, a hospital facility or a shipping yard. The classicexample is having a system that can monitor the exact location of thecrash cart within the hospital so that when there is a cardiac arrestthe hospital staff doesn't waste time locating the device. The accuracyrequirements for these use cases are very demanding, typically callingfor 1-3 meter accuracy. These systems use a variety of techniques tofine tune their accuracy including conducting detailed site surveys ofevery square foot of the campus to measure radio signal propagation.They also require a constant network connection so that the access pointand the client radio can exchange synchronization information similar tohow A-GPS works. While these systems are becoming more reliable forindoor use cases, they are ineffective in any wide-area deployment. Itis impossible to conduct the kind of detailed site survey requiredacross an entire city and there is no way to rely on a constantcommunication channel with 802.11 access points across an entiremetropolitan area to the extent required by these systems. Mostimportantly, outdoor radio propagation is fundamentally different thanindoor radio propagation, rendering these indoor positioning techniquesalmost useless in a wide-area scenario.

There are millions of commercial and private WLANs deployed so far andthis number is growing everyday. Thus, WLAN access points are used toestimate the location of WLAN-enabled mobile devices.

SUMMARY

In one aspect, the invention features a method of estimating an expectederror of a position estimate for use in a WLAN positioning system thatestimates the position of a WLAN-enabled device. The WLAN-enabled devicereceives signals transmitted by a WLAN access point in range of theWLAN-enabled device. The method estimates the position of theWLAN-enabled device based on the received signals from the WLAN accesspoint in range of the WLAN enabled device. The method also estimates anexpected error of the position estimate based on characteristics of theWLAN access point in range of the WLAN enabled device, wherein theexpected error predicts a relative accuracy of the position estimate.

In another aspect of the invention, the position estimate of theWLAN-enabled device is based on signals from more than one WLAN accesspoint in range of the WLAN-enabled device. In a further aspect, theexpected error of the position estimate is based on characteristics frommore than one WLAN access point in range of the WLAN-enabled device.

In yet another aspect, the expected error of the position estimate isbased on the number of access points used to estimate the position ofthe WLAN enabled device.

In another aspect of the invention, each of the WLAN access points hasan associated signal coverage area. The expected error of the positionestimate is based on at least one of the signal coverage areas of theWLAN access points used to estimate the position of the WLAN-enableddevice.

In a further aspect of the invention, the expected error of the positionestimate is based on the smallest signal coverage area of the WLANaccess points used to estimate the position of the WLAN-enabled device.

In yet a further aspect of the invention, the coverage area for eachWLAN access point is estimated by determining geographic locations atwhich a WLAN-enabled device receives a signal from the WLAN accesspoint, determining the standard deviation of the coverage area based onthe determined geographic locations, and estimating the coverage area ofthe WLAN access point based on the standard deviation of the coveragearea.

In one aspect of the invention, each of the WLAN access points has ageographic position, and the expected error of the position estimate isbased on the spatial spread of the geographic positions of the accesspoints used to estimate the position of the WLAN-enabled device. Thespatial spread is based on a distance between the geographic positionsof the WLAN access points used to estimate the position of theWLAN-enabled device.

In another aspect of the invention, a position estimate is used inconjunction with other position estimates to derive at least one ofposition, speed, and direction of travel of the WLAN-enabled device andthe weight given to the position estimate is based on the expected errorof the position estimate. In one aspect, the position estimate is usedonly if the expected error of the position estimate is lower than apredetermined threshold. In a further aspect, at least one of the otherposition estimates is based on received signals from WLAN access pointsin range of the WLAN enabled device. In other aspects, at least one ofthe other position estimates is provided by a GPS-based positioningsystem.

In yet a further aspect, the invention features a system for estimatingan expected error of a position estimate for use in a WLAN positioningsystem that estimates the position of a WLAN-enabled device. The systemincludes: a WLAN-enabled device for receiving signals transmitted by aWLAN access point in range of the WLAN-enabled device, positionestimating logic for estimating the position of the WLAN-enabled devicebased on the received signals from the WLAN access point in range of theWLAN enabled device, and error estimating logic for estimating anexpected error of the position estimate based on characteristics of theWLAN access points in range of the WLAN enabled device, wherein theexpected error predicts a relative accuracy of the position estimate.

BRIEF DESCRIPTION OF DRAWINGS

In the drawings,

FIG. 1 illustrates certain embodiments of a WLAN positioning system.

FIG. 2 illustrates an example of a WLAN-enabled mobile device andsurrounding access points and their corresponding coverage areas.

FIG. 3 illustrates an example of the impact of the spatial spread ofdetected WLAN access points on the accuracy of position estimation of aWLAN-enabled mobile device.

FIG. 4 illustrates an example of the impact of the number of detectedWLAN access points on the accuracy of a position estimate of aWLAN-enabled mobile device.

DETAILED DESCRIPTION

Preferred embodiments of the invention estimate the error associatedwith a derived position provided by a WLAN positioning system. Theincorporated patent applications describe a WLAN-based positioningsystem that can derive and provide estimated positions for WLAN-enableddevices.

Preferred embodiments of the invention determine and update the expectederror of position estimates of a WLAN-based positioning system that usepublic and private WLAN access points. (Note that 802.11, 802.11b,802.11e, 802.11n, and WiFi are examples of WLAN standards.) The user'smobile device periodically scans and detects public and private WLANaccess points and also logs signals characteristics of each of the WLANaccess points, for example, Received Signal Strength (RSS), TimeDifference of Arrival (TDOA), or Time difference of Arrival (TOA)corresponding to each of the WLAN access points. In some embodiments,the mobile device itself determines the expected error of a positionestimate. In other embodiments, the mobile device sends the results ofscanning the surrounding WLAN access points to a central site where acentral server determines the expected error.

The expected error of a WLAN position estimate may be used to quantifythe quality of the position estimate. This may be useful when multipleposition estimates are combined or when the WLAN-based positionestimates are combined with other position estimation techniques, e.g.,GPS position estimation. The expected error of each position estimatemay be used as a weighting factor when a series of position estimatesare combined. For example, in order to increase the accuracy of singleposition estimate, multiple position estimates may be a weightedaverage. In this case, the expect error of each position estimate isused as a weight in a weighted average calculation.

In addition, a series of position estimates may be combined to derivethe mobile device's speed of travel or bearing. When such a series ofposition estimates are combined, the expected error of each estimate isused as a corresponding quality metric of the estimation, which enablesthe optimal combination of the series of position estimates based ontheir quality.

For example, in a series of ten position estimates, assume all but theseventh position estimate have a relatively low expected error ofposition estimation, while the seventh position estimate has arelatively high expected error. When the mobile device uses this seriesof position estimates to derive the speed of the mobile device, themobile device may exclude the seventh position estimate in the speeddetermination because its relatively high expected error value indicatesthat that particular position estimate is of low quality and, thus, maybe unreliable.

The expected error of a position estimates may also be used to determinethe expected error after combining the position estimate results. Forexample, if the position estimate results are used to determine speed oftravel, the expected errors of individual position estimates arecombined to determine the estimation error of the speed of travel.

Certain embodiments of the invention build on techniques, systems andmethods disclosed in earlier filed applications, including but notlimited to U.S. patent application Ser. No. 11/261,848, entitledLocation Beacon Database, U.S. patent application Ser. No. 11/261,898,entitled Server for Updating Location Beacon Database, U.S. patentapplication Ser. No. 11/261,987, entitled Method and System for Buildinga Location Beacon Database, and U.S. patent application Ser. No.11/261,988, entitled Location-Based Services that Choose LocationAlgorithms Based on Number of Detected Access Points Within Range ofUser Device, all filed on Oct. 28, 2005, and also including but notlimited to U.S. patent application Ser. No. 11/430,224, entitledCalculation of Quality of WLAN Access Point Characterization for Use ina WLAN Positioning System, and U.S. patent application Ser. No.11/430,222, entitled Estimation of Position Using WLAN Access PointRadio Propagation Characteristics in a WLAN Positioning System, bothfiled on May 8, 2006, the contents of which are hereby incorporated byreference in their entirety. Those applications taught specific ways togather high quality location data for WLAN access points so that suchdata may be used in location based services to determine the geographicposition of a WLAN-enabled device utilizing such services and techniquesof using

said location data to estimate the position of a system user. Thepresent techniques, however, are not limited to systems and methodsdisclosed in the incorporated patent applications. Thus, while referenceto such systems and applications may be helpful, it is not believednecessary to understand the present embodiments or inventions.

FIG. 1 depicts a WLAN positioning system (WPS). The positioning systemincludes positioning software [103] that resides on a user device [101].Throughout a particular target geographical area, there are fixedwireless access points [102] that broadcast information usingcontrol/common channel broadcast signals. The client device monitors thebroadcast signal or requests its transmission via a probe request. Eachaccess point contains a unique hardware identifier known as a MACaddress. The client positioning software 103 receives signal beaconsfrom the 802.11 access points 102 in range and determines the geographiclocation of the user device 101 using characteristics from the signalbeacons. Those characteristics include the access point's MAC addressand the strengths of the signal reaching the client device. The clientsoftware compares the observed 802.11 access points with those in itsreference database [104] of access points, which may or may not resideon the device as well (i.e., in some embodiments, the reference databasecan be remotely located). The reference database contains the estimatedgeographic locations and power profile of all the access points thegathering system has collected. The power profile may be generated froma collection of readings that represent the power of the signal fromvarious locations. Using these known locations and power profiles, theclient software determines the relative position of the user device[101] and determines its geographic coordinates in the form of latitudeand longitude readings. Those readings are then provided tolocation-based applications such as friend finders, local search websites, fleet management systems and E911 services.

Preferred embodiments of the invention may be used in a WLAN-enableddevice to determine and update expected error of position estimates. Forexample, techniques in accordance with embodiments of the invention maybe incorporated in logic embedded in positioning software [103] of theWLAN-enabled device of FIG. 1.

Under one embodiment of the invention, the expected error of a positionestimate of a WLAN-enabled mobile device is estimated based on thecoverage area of all of the access points used to locate theWLAN-enabled mobile device. In other words, if all the detected accesspoints are considered, the signal foot prints (or the coverage areas) ofthe detected access points are used to determine the expected error ofthe position estimate. In one illustrative implementation, the expectederror of the position estimate is bounded by the smallest coverage areaof the access points that are used to estimate the location of aWLAN-enabled mobile device. Therefore, the method is based on findingthe smallest coverage area among the access points that are used toestimate the location of an end user in a WLAN-based positioning system.The expected error is directly correlated with the smallest coverage ofdetected WLAN access points. If the expected error is denoted by e, andthe smallest coverage is denoted by C_(min), the error can be written asa function of the smallest coverage as follows:

e∝f(C _(min))|

The notation ∝ means direct dependency. One example of the function isas follows:

e=K _(c) C _(min)|

The parameter K_(c) is a constant number to scale the value of smallestcoverage area to the actual error in meters. The parameter K_(c)translates the minimum coverage in m² to error in meters. The parameterK_(c) is found empirically by considering enough samples in the entirecoverage area and finding the actual error and the Cmin value. Theactual error can be determined by comparing the estimated positionprovided by the WLAN positioning system with a known position.

The coverage area or the footprint of a WLAN access point is defined asthe area in which a WLAN-enabled mobile device can detect the particularaccess point. The coverage area of an access point is found bysystematically scanning a target geographical area containing manyaccess points and recording Received Signal Strength (RSS) samples atknown locations. When all the samples of a given access point areconsidered, the standard deviation of the location of the RSS samples isused as an indicator of the size of the coverage area of the accesspoint. In some embodiments, all RSS samples are considered. In otherimplementations, some RSS samples are ignored if the RSS is below agiven threshold. If the total number of RSS samples of an access pointis denoted by M and the corresponding location of RSS sample i isdenoted by (x_(i), y_(i)), the standard deviation, σ, of coverage areais calculated as follows:

σ=√{square root over (σ_(x) ²+σ_(y) ²)},

in which σ_(x) and σ_(y) are the standard deviation of x_(i) and y_(i)over all M samples, respectively.

FIG. 2 illustrates an example of a WLAN-enabled mobile device and WLANaccess points in its surroundings. In FIG. 2, the user [201] detectsWLAN access points [202 a-d] in range and estimates its location byusing the detected WLAN access points as reference points. The accesspoints [202 a-d] in range have different coverage sizes [203 a-d]. Theestimation error is bounded by the minimum coverage [204] of thedetected access points [202 a-d]. For example, if the radius of thecoverage area [203 a] of the access point [202 a] is 100 meters, themaximum estimation error corresponding to the position of user [201] is100 meters.

Under other embodiments of the invention, the expected error of aposition estimation is estimated based on how the detected access pointsare spatially spread, i.e., the distance between the geographic locationof the detected access points. An example of the impact of the spatialspread of the detected access points on the position estimation error isillustrated in FIG. 3. FIG. 3 illustrates a WLAN-enabled mobile device[301] with detected access points [302] and WLAN-enabled mobile device[303] with detected access points [304]. The estimated location ofmobile devices [301] and [303] are shown by circles [305] and [306]respectively. The figure illustrates a smaller estimation error formobile device [301] with a relatively smaller spatial spread of detectedaccess points than mobile device [303], which has a relatively largerspatial spread of detected access points. The spatial spread of accesspoints can be measured by the standard deviation of their location inthe X and Y axis, σ_(sx) and σ_(sy), and then finding the total spatialspread standard deviation as follows:

σ_(s)=√{square root over (σ_(sx) ²+σ_(sy) ²)}

The expected error directly correlates with the standard deviation ofspatial spread. So,

e∝f(σ_(s)).

An example of the above function is as follows:

e=K _(s)σ_(s) ²

The parameter K_(s) is a constant number to scale the output value toerror in meters. The parameter K_(s) translates the square of thestandard deviation in m² to error in meters. The parameter K_(c) isfound empirically by considering enough samples in the entire coveragearea and finding the actual error and the standard deviation squarevalue. Error in meters is calculated by using the technique describedabove.

s Under other embodiments of the invention, the expected error of aWLAN-enabled mobile device in a WLAN positioning system is estimatedbased on the number of access points that are detected. As illustratedin FIG. 4, the expected error decreases as the number of detected accesspoints increases. FIG. 4 shows two WLAN-enabled mobile devices [401] and[403], with detected access points [402] and [404], respectively, andestimated positions [405] and [406], respectively. The figureillustrates that the expected error of position estimation is lower forWLAN-enabled mobile device [403] because of the greater number of accesspoints used to estimate it position. Therefore, the expected error iscorrelated with the inverse of the number of detected access points. IfN denotes the number of detected access points that are used to locatean end user, the expected error can be written as follows:

$e \propto {f( \frac{1}{N} )}$

An example of the above function is as follows:

$e = {K_{N}\frac{1}{\sqrt{N}}}$

The parameter K_(N) is a constant number to scale the output of theequation to error in meters. In terms of units, the parameter K_(N) isin meters. The parameter K_(N) is found empirically by consideringenough samples in the entire coverage area and finding the actual errorand the N value. Error in meters is calculated by using the techniquedescribed above.

Under other embodiments of the invention, the expected error of aWLAN-enabled mobile device in a WLAN positioning system is estimatedbased on combining multiple correlated parameters with error. The threeparameters correlated with the expected error of a position estimate areas follows: (1) the smallest coverage of detected access points,C_(min), (2) one over square root of number of detected access points,1/√N, (3) square of spatial spread of detected access points, σ_(s) ².

The above parameters are correlated with the expected error, but interms of the absolute value they have different dynamic ranges. In orderto be able to combine them, their absolute values have to be normalizedfirst. Normalization of the parameters is achieved by dividing them bythe standard deviation of their dynamic range. The dynamic range is thelargest and smallest absolute values of all of the access points in agiven coverage area.

The normalized parameters can be simply averaged or they can be weightedaccording to the accuracy with which each parameter predicts theexpected error and then averaged, which is called the weighted average.Weighting each component of error according to its accuracy of errorprediction is more desirable and it is the optimum combining method. Thenext step in the weighted average approach is defining a metric for eachof the parameters that measures the accuracy of the error prediction.

The correlation of each parameter with the error measures the accuracyof the error prediction of the particular error estimation method. Thesecorrelation coefficients are used to weight each method in the weightedaverage calculation. A correlation coefficient is a statisticalparameter, and it is determined globally for each parameter based on asufficient number of samples for the targeted geographic area by findingthe actual error of a position estimate and also finding the estimatedvalue of the parameter and then determining the correlation coefficient.Therefore, the correlation coefficient shows the statistical correlationof an estimation parameter with estimation error, and it does not showexactly the quality of one sample of the parameter. For example, oneinstance of a position determination might have a very small estimationerror, but the smallest coverage area of the detected access pointsmight be relatively large. In this example, the smallest coverage areaof the detected access points is not a good indicator of the error, butit is still weighted with the same correlation coefficient as othersamples. Therefore, the expected error using weighted average of theerror parameters is written as follows:

$e \propto {\lbrack {{C_{c}\frac{C_{\min}}{\sigma ( C_{\min} )}} + {C_{N}\frac{\sqrt{1/N}}{\sigma ( \sqrt{1/N} )}} + {C_{s}\frac{\sigma^{2}}{\sigma ( \sigma_{s}^{2} )}}} \rbrack \times \frac{1}{( {C_{c} + C_{N} + C_{s}} )}}$

In the above equation, the standard deviation operator is shown with aand the correlation coefficients for C_(min), N, and σ_(s) are shownwith C_(c), C_(N), and C_(s), respectively. The correlation coefficientsare unitless. The correlation coefficients are found empirically byconsidering enough samples in the entire coverage area and comparing theexpected error with the actual error for each sample.

Under other embodiments of the invention, the expected error of aposition estimate is found in meters from a parameter that is correlatedwith the expected error. Assuming that there is a parameter correlatedwith the expected error, the estimation error in meters is found bymapping the distribution of the error parameter into the actual distanceerror in meters as found during scanning the targeted geographic area.Therefore, if error in meters is denoted by d_(e), it is found as theresult of the mapping and can be calculated as follows:

$d_{e} = {{( \frac{e - e}{\sigma (e)} ){\sigma ( d_{e} )}} + d_{e}}$

Note that the average value of a random process is shown with a bar onthe variable and the standard deviation operator is shown with a. Theaverage and the standard deviation of d_(e) and e are found empiricallyby considering the1 distribution of these parameters over samples thatare collected from the entire coverage area. An example of the standarddeviation and the average value of the parameters are as follows:

σ(C_(min)) = 2.7546${\sigma ( \sqrt{\frac{1}{N}} )} = 0.1721$$\sigma( {\sigma_{s_{5}}^{2} = {{3.8707 \times 10^{- 7}\overset{\_}{e}} = {{1.5613\sigma_{e}} = {{0.7458\overset{\_}{d_{e}}} = {{38.1\mspace{14mu} m\sigma_{d_{e}}} = {29.0\mspace{14mu} m}}}}}} $

Note that the standard deviation of spatial spread of detected accesspoints is determined based on the latitude and longitude of accesspoints.

An example of the correlation coefficients is as follows:

0.30≦C _(c) ,C _(N) ,C _(x)≦0.37

It will be appreciated that the scope of the present invention is notlimited to the above described embodiments, but rather is defined by theappended claims; and that these claims will encompass modifications ofand improvements to what has been described.

What is claimed is:
 1. A method of estimating and using an expectederror of a position estimate of a wireless local area network(WLAN)-enabled mobile device produced by a WLAN positioning system, themethod comprising: receiving, by the WLAN-enabled mobile device, signalstransmitted by a plurality of WLAN access points in range of theWLAN-enabled device; estimating the position of the WLAN-enabled devicebased on the received signals from the WLAN access points in range ofthe WLAN-enabled device; estimating an expected error of the positionestimate based on at least one of a spatial spread associated withgeographic positions of the WLAN access points, signal coverage areas ofthe WLAN access points, or a number of the WLAN access points; and usingthe expected error in providing one or more location-based services to auser of the WLAN-enabled mobile device.
 2. The method of claim 1,wherein the expected error is represented in terms of distance.
 3. Themethod of claim 1, wherein the expected error is based on the spatialspread associated with geographic positions of the WLAN access points.4. The method of claim 3, wherein the expected error is directlyproportional to a square of a standard deviation of the spatial spreadof the geographic positions of the WLAN access points.
 5. The method ofclaim 1, wherein the expected error is based on signal coverage areas ofthe WLAN access points.
 6. The method of claim 5, wherein the expectederror is calculated based on a smallest signal coverage area of a WLANaccess point of the WLAN access points.
 7. The method of claim 6,wherein the expected error is directly proportional to the smallestsignal coverage area.
 8. The method of claim 1, wherein the expectederror is based on the number of the WLAN access points.
 9. The method ofclaim 8, wherein the expected error is inversely proportional to thesquare root of the number of WLAN access points.
 10. The method of claim1 wherein the using the expected error comprises: excluding the positionestimate of the WLAN-enabled mobile device from a combination ofposition estimates used to produce a position of WLAN-enabled mobiledevice to be used in the one or more location-based services.
 11. Themethod of claim 1, wherein the using the expected error comprises:weighting the position estimate of the WLAN-enabled mobile device in acombination of position estimates used to produce a position ofWLAN-enabled mobile device to be used in the one or more location-basedservices.
 12. A system for estimating and using an expected error of aposition estimate of a wireless local area network (WLAN)-enabled mobiledevice, the system comprising: a WLAN-enabled mobile device configuredto receive signals transmitted by a plurality of WLAN access points inrange of the WLAN-enabled mobile device; positioning software residingon the WLAN-enabled mobile device, the positioning software whenexecuted operable to: estimate the position of the WLAN-enabled devicebased on the received signals from the WLAN access points in range ofthe WLAN-enabled device; estimate an expected error of the positionestimate based on at least one of a spatial spread associated withgeographic positions of the WLAN access points, signal coverage areas ofthe WLAN access points, or a number of the WLAN access points; and usethe expected error in in determining a position used in one or morelocation-based services provided to a user of the WLAN-enabled mobiledevice.
 13. The system of claim 12, wherein the expected error isrepresented in terms of distance.
 14. The system of claim 12, whereinthe expected error is based on the spatial spread associated withgeographic positions of the WLAN access points.
 15. The system of claim12, wherein the expected error is based on signal coverage areas of theWLAN access points.
 16. The system of claim 12, wherein the expectederror is based on the number of the WLAN access points.
 17. Anon-transitory device-readable medium with software stored thereon thatwhen executed on a wireless local area network (WLAN)-enabled device isoperable to: estimate the position of the WLAN-enabled device based onreceived signals from WLAN access points in range of the WLAN-enableddevice; estimate an expected error of the position estimate based on atleast one of a spatial spread associated with geographic positions ofthe WLAN access points, signal coverage areas of the WLAN access points,or a number of the WLAN access points; and using the expected error inproviding one or more location-based services to a user of theWLAN-enabled mobile device.
 18. The non-transitory device-readablemedium of claim 17, wherein the expected error is based on the spatialspread associated with geographic positions of the WLAN access points.19. The non-transitory device-readable medium of claim 17, wherein theexpected error is based on signal coverage areas of the WLAN accesspoints.
 20. The non-transitory device-readable medium of claim 17,wherein the expected error is based on the number of the WLAN accesspoints.